Square wave voltammetry with multivariate calibration tools for determination of eugenol, carvacrol and thymol in honey

Abstract

The simultaneous determination of eugenol (EU), thymol (Ty) and carvacrol (CA) in honey samples, employing square wave voltammetry (SWV) and chemometrics tools, is informed for the first time. For this purpose, a glassy carbon electrode (GCE) was used as working electrode. The operating conditions and influencing parameters (involving several chemical and instrumental parameters) were first optimized by cyclic voltammetry (CV). Thus, the effects of the scan rate, pH and analyte concentration on the electrochemical response of the above mentioned molecules were studied. The results show that the electrochemical responses of the three compounds are very similar and that the voltammetric traces present a high degree of overlap under all the experimental conditions used in this study. Therefore, two chemometric tools were tested to obtain the multivariate calibration model. One method was the partial least squares regression (PLS-1), which assumes a linear behaviour. The other nonlinear method was an artificial neural network (ANN). In this last case we used a supervised, feed-forward network with Levenberg-Marquardt back propagation training. From the accuracies and precisions analysis between nominal and estimated concentrations calculated by using both methods, it was inferred that the ANN method was a good model to quantify EU, Ty and CA in honey samples. Recovery percentages were between 87% and 104%, except for two samples whose values were 136% and 72%. The analytical methodology was simple, fast and accurate.